End‑to‑end delivery of AI features—data pipelines, services, and clean UIs—built with reliable, modern tooling. We design pragmatic architectures, keep the surface area small, and ship in tight 2–6 week iterations. Every change is tested and observable; costs, latency, and traces are visible from day one. We bias to guardrails, feature flags, and fast rollbacks so teams can move quickly without surprises. The result is software your team can operate: secure, measurable, and built to last.
Why it matters
Reliable engineering converts AI from demos into dependable systems—fast to ship, easy to operate, and built to last. Without it, teams end up with brittle scripts, opaque agents, and surprise bills. We put guardrails around data and operations, instrument for cost and error budgets, and design for rollback so you can move fast without burning trust.
What we do
Production‑grade AI features
From “button‑click” copilots to background agents that file tickets, sync records, or draft customer responses. We design around measurable outcomes: cycle time, cost‑to‑serve, error rate, and user satisfaction.
Typical delivery includes: typed SDKs, API contracts, evaluation datasets, and dashboards so teams can see what the system is doing—every step, every call, every cost.
Data pipelines & services
Ingest data from CRMs, ERPs, and file stores; normalize, enrich, and expose it through clean services for apps and agents.
Retrieval stays PII‑aware, filtered by role, tenant, and purpose—blending vector search with relational lookups for ground truth.
Interfaces people actually use
Modern, accessible UIs with clear affordances and “why” explanations. We bias to fast feedback: inline diffs, traceable actions, and one‑click rollbacks when humans need the final say.
How we work
Small scope, shipped fast. We run tight iterations (usually 2–6 weeks), keep the surface area sane, and instrument everything. You get a working slice in production, not a slide deck.
Scope ≤2 weeks.
Pick a workflow, define success metrics, and confirm where humans approve exceptions.
Prototype.
Clickable UI + stubbed services; we validate the UX before we automate.
Instrument.
Add eval datasets, traces, and cost/latency budgets; wire logs to dashboards.
Pilot.
Roll to a small group with feature flags, feedback capture, and safe fallbacks.
Scale & hand‑off.
Harden, document, and hand you the keys. Your team can own it.
Examples
Permit & property ops
Upload plan sets → extract structured data → flag inconsistencies → draft permit forms. Humans approve, system files and tracks.
Back‑office automations
Agents reconcile purchase orders against deliveries, escalate anomalies to humans, and create clean audit trails for later review.
Private data assistants
On‑brand assistants grounded in your knowledge that cite sources, respect permissions, and explain every answer.
Handoff & Deliverables
You keep the repo, the infra‑as‑code, the dashboards, and the playbooks. We ship traces, evaluation datasets, cost/latency budgets, and runbooks that explain how to operate and extend the system. Release toggles and rollback paths are documented in plain English, with ownership and escalation mapped to your team. If you want ongoing help, we can operate via a light SLA—or we bow out cleanly.
